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                                <h1 id="智源评测报告">智源评测报告</h1>
<p>作者：<a href="https:/https://flageval.baai.ac.cn/" target="_blank">FlagEval</a> </p>
<h2 id="关于本书">关于本书</h2>
<p>本技术报告详细介绍了智源人工智能研究院历经3个月筹备的大模型评测，对评测方法、流程和结果进行系统说明。</p>
<p>本次评测共使用超8万道考题，其中含4000+原创未公开主观题，对全球40余家大模型企业或研究团队的共计140余个大模型（其中108个开源模型，和33个闭源模型）进行了评测，包括大语言模型（对话模型和基础模型）、视觉语言大模型、文生图模型及文生视频模型。同时，首次联合权威教育机构进行大模型K12学科评测，将模型与人类学生的结果进行对比分析，为准确把握模型能力进展提供参考。 </p>
<p>本次评测结果显示，国内大语言模型在中文语境下的综合表现基本接近国际一流水平，但存在明显的能力不均衡情况；视觉语言模型（图文问答）开源模型与商业模型平分秋色，深度专业图理解是需突破的短板，国产模型在图文问答有不错表现；文生图模型的客观评测指标可靠性不足，国内外模型能力差异点显著；文生视频模型整体能力仍需提升，Sora显示出明显优势。大模型在学科测验上的最好表现尚未达到人类学生平均水平，学科上文科类学科好于理科类学科表现，图表理解能力仍有很大提升空间。</p>
<!-- <img style="float: right;margin-left: auto;  margin-right: auto;" src="nndl2.jpg"> -->
<h2 id="概要">概要</h2>
<p><strong>全文内容</strong> <a href="https://github.com/FlagOpen/FlagEval/blob/master/AI%E5%A4%A7%E6%A8%A1%E5%9E%8B%E8%83%BD%E5%8A%9B%E5%85%A8%E6%99%AF%E6%89%AB%E6%8F%8F.pdf" target="_blank">pdf</a> (updated 2024-07-13)</p>
<!-- ### 章节内容

1. 绪论[[ppt](./ppt/chap-绪论.pptx)] 
2. 机器学习概述  [[ppt](./ppt/chap-机器学习概述.pptx)] 
3. 线性模型 [[ppt](./ppt/chap-线性模型.pptx)]  
4. 前馈神经网络 [[ppt](./ppt/chap-前馈神经网络.pptx)] 
5. 卷积神经网络 [[ppt](./ppt/chap-卷积神经网络.pptx)]  
6. 循环神经网络 [[ppt](./ppt/chap-循环神经网络.pptx)]   
7. 网络优化与正则化  [[ppt](./ppt/chap-网络优化与正则化.pptx)]  
8. 注意力机制与外部记忆 [[ppt](./ppt/chap-注意力机制与外部记忆.pptx)]  
9. 无监督学习 [[ppt](./ppt/chap-无监督学习.pptx)] 
10. 模型独立的学习方式 [[ppt](./ppt/chap-模型独立的学习方式.pptx)] 
11. 概率图模型 [[ppt](./ppt/chap-概率图模型.pptx)] 
12. 深度信念网络 [[ppt](./ppt/chap-深度信念网络.pptx)] 
13. 深度生成模型[[ppt](./ppt/chap-深度生成模型.pptx)] 
14. 深度强化学习  [[ppt](./ppt/chap-深度强化学习.pptx)] 
15. 序列生成模型 [[ppt](./ppt/chap-序列生成模型.pptx)]     一个过时版本：[词嵌入与语言模型](./old-chap/chap-语言模型与词嵌入.pdf)
16. 数学基础  -->
<h2 id="引用信息">引用信息</h2>
<pre><code>@book{flageval2024,
title = {AI大模型能力全景扫描},
year = {2024},
author = {FlagEval},
address = {北京},
url = {https://github.com/FlagOpen/FlagEval/blob/master/AI%E5%A4%A7%E6%A8%A1%E5%9E%8B%E8%83%BD%E5%8A%9B%E5%85%A8%E6%99%AF%E6%89%AB%E6%8F%8F.pdf},
}
</code></pre><h2 id="反馈意见">反馈意见</h2>
<p>如果您有任何意见、评论以及建议（先确认最新版本中是否已经修正），请通过GitHub的<a href="https://github.com/FlagOpen/FlagEval/issues" target="_blank">Issues</a>页面进行反馈。如果错误比较重要，我会在本书中进行致谢。</p>
<p>反馈意见包括但不限于：（因为分开排版关系，页码错误请忽略。）</p>
<ul>
<li>打字错误</li>
<li>描述错误: 比如“感知器是非线性分类器”</li>
<li>评论</li>
<li>建议</li>
</ul>
<p>非常感谢！</p>

                                
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